Data Engineer - Industrials & Energy Sector - Senior Manager - Consulting - Location Open

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better. Join us and build an exceptional experience for yourself, and a better working world for all.   The exceptional EY experience. It's yours to build.   EY focuses on high-ethical standards and integrity among its employees and expects all candidates to demonstrate these qualities.  

Data Engineering Senior Manager – EY: This position can be anywhere in the country (primary: NY).

 

The Opportunity

EY's Industrial Product team is seeking a Senior Manager in Data Engineering focusing on helping our clients with future forward data strategy and data management in the advanced manufacturing sector, including vehicle automation, connectivity, electrification, and enterprise AI. This leadership role requires a seasoned professional with a strong background in data engineering to guide the development of cloud-based solutions, drive pre-sales efforts, and manage complex projects that meet organizational goals.

 

Your Key Responsibilities

Strategic Oversight: Lead the strategic design and implementation of data engineering initiatives, ensuring alignment with business objectives and adherence to best practices in data architecture and ETL principles.

Cloud Solutions Leadership: Oversee the design and maintenance of scalable data pipelines and architectures using cloud platforms such as AWS, Azure, and Databricks. Ensure solutions accommodate increasing data sources, volumes, and complexity.

Solution Recommendation: Utilize your strong background to recommend and lead cloud-based and data engineering solutions, addressing complex technical challenges and ensuring optimal performance.

Pre-Sales and RFPs: Engage in pre-sales activities and contribute to RFP responses by developing and articulating advanced data engineering solutions that address client needs and demonstrate the value of our offerings.

AI/ML and Advanced Analytics: Collaborate with AI/ML engineers to design and implement data solutions that support machine learning, large language models (LLM), and advanced analytics. Integrate AI/ML capabilities into data engineering workflows.

Data Requirements and Validation: Define data requirements, manage the ingestion of structured and unstructured data, and validate data using tools and methodologies in a Big Data environment.

Data Quality and Reconciliation: Implement processes for data reconciliation and quality monitoring, ensuring production data is accurate and available for stakeholders, downstream systems, and business processes.

Technical Leadership: Evaluate, implement, and deploy emerging tools and processes to enhance data engineering capabilities. Develop and deliver communication and education plans on data engineering standards and practices.

Digital and Cloud Modernization: Lead digital transformation and cloud modernization efforts, leveraging cloud-native technologies and practices to improve data engineering solutions and processes.

Team Management: Mentor and lead a team of data engineers, fostering a culture of innovation, continuous improvement, and professional development.

Stakeholder Collaboration: Partner with Business Analytics, Solution Architects, Data Scientists, and AI/ML engineers to design and deliver data solutions that support advanced analytics, machine learning, and predictive modelling.

 

Skills and Attributes for Success

Cloud Solutions Expertise: Strong background in designing and implementing cloud-based data solutions using AWS, Azure, Databricks, and other relevant cloud technologies.

AI/ML Integration: Experience with AI/ML technologies, including machine learning, large language models (LLM), and integration of